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[ASK AN EXPERT] What are Predictive Analytics for Planned Giving?

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Our Ask An Expert series features real questions answered by Claire Axelrad, J.D., CFRE, our very own Fundraising Coach, also known as Charity Clairity.

Today’s question comes from a nonprofit leader who needs advice on identifying planned giving prospects through predictions and analytics.  

Dear Charity Clairity,

My board wants us to develop more planned gifts and I’m wondering about purchasing planned giving analytics so we can better identify likely prospects. What exactly is this, and does it work?

— Clueless

Dear Clueless,

What you’re asking about is called predictive modeling. There are companies like Donor Search or Target Analytics (I’m not recommending any particular product) who will run your database through a series of other databases that screen for wealth (income and assets), financial behavior, political giving, charitable giving and so forth while also determining general demographics and propensities of donors in your own database such as age (or life stage), gender, race, religion, income levels, education, areas of interest, timeliness and frequency of giving, volunteerism, other affiliations, etc. 

Your data is melded with general database data to come up with profiles that identify those with particular “planned giving likelihood” for you. Note you can screen for other factors, such as “major gift likelihood” as well. Each donor will receive a “likelihood” score. You can then run reports based on those scores, seeking to begin prospect identification, cultivation and solicitation plans with those at the top.

You can also purchase additional software, like Wealth Engine, Donor Search and others, to help you do further research on prospects you’ve identified as having high potential. This may help you better determine their capacity and predisposition to give so you can more appropriately tailor your approach and ask.

You do have to take these outcomes with a large shaker of salt. 

  • Some of the information will be outdated. 
  • Some of it will be incomplete. Wealthy people are pretty good at hiding assets if they want to. 
  • Some of it will be misleading. Someone in San Francisco or New York City who owns a home may get a high score simply by virtue of home ownership. Yet this may be their only asset, which they intend to pass to their heirs, and is not necessarily an indicator or significant wealth or philanthropic inclination.

One of the best outcomes I’ve found from purchasing these services is making leadership confident you have real legacy giving potential. Some folks are more easily persuaded by data than anything else! Once you have buy-in that a legacy giving program makes sense for you, you can stop arguing about if and begin to robustly dig in to when, what, who, where and how.

I hope this helps to clairify things!

— Charity Clairity

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  • Linda Garrison, CFRE

    Claire, great comments. May I add that a true predictive model uses the people in the database who are already legacy donors, major donors or whatever the model’s target. The model is built after screening. The statistician then calculates the weight of various factors and applies the most strong common factors to the rest of the database. The file is then broken into deciles (10 bundles of an equal amount of donors) and finds those who most resemble the existing donors. You’re right about screening for sure. Screening provides some guidance, modeling a bit more, but the real art of development is relationship building.
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